International Journal of Sports Physiology and Performance, 2014, 9, 993-999 http://dx.doi.org/10.1123/ijspp.2013-0486 ©2014 Human Kinetics, Inc.

Jumping and Hopping in Elite and Amateur Orienteering Athletes and Correlations to Sprinting and Running

Kim Hebert-Losier, Kurt Jensen, and Hans-Christer Holmberg

Purpose: Jumping and hopping are used to measure lower-body muscle power, stiffness, and stretch-shortening-cycle utilization in sports, with several studies reporting correlations between such measures and sprinting and/or running abilities in athletes. Neither jumping and hopping nor correlations with sprinting and/or running have been examined in orienteering athletes. Methods: The authors investigated squat jump (SJ), countermovement jump (CMJ), standing long jump (SLJ), and hopping performed by 8 elite and 8 amateur male foot-orienteering athletes (29 ± 7 y, 183 ± 5 cm, 73 ± 7 kg) and possible correlations to road, path, and forest running and sprinting performance, as well as running economy, velocity at anaerobic threshold, and peak oxygen uptake (VCbpeak) from treadmill assessments. Results: During SJs and CMJs, elites demonstrated superior relative peak forces, times to peak force, and prestretch augmentation, albeit lower SJ heights and peak powers. Between-groups differences were unclear for CMJ heights, hopping stiffness, and most SLJ parameters. Large pairwise correlations were observed between relative peak and time to peak forces and sprinting velocities; time to peak forces and running velocities; and prestretch augmentation and forest-running velocities. Prestretch augmentation and time to peak forces were moderately correlated to V 02peak- Correlations between running economy and jumping or hopping were small or trivial. Conclusions: Overall, the elites exhibited superior stretch-shortening-cycle utilization and rapid generation of high relative maximal forces, especially vertically. These functional measures were more closely related to sprinting and/or running abilities, indicating benefits of lower-body training in orienteering.

Keywords: athletic performance, foot orienteering, jump tests, off-road running, stiffness

Jump tests are used in several sports to assess lower-body muscle power,1 vertical stiffness,2 and stretch-shortening-cycle utilization,3 with jump performance often correlating with or predicting individual sprinting and/or running abilities.1-4-6 More precisely, horizontal- and vertical-jump distances of physically active individuals are strongly correlated with their 20-m-sprint times,4 and peak CMJ forces strongly predict maximal 10-m-sprint velocities of track and field athletes.6 Peak CMJ forces5 and leg stiffness1-5 also exhibit strong relationships with running economy(RE).

In foot orienteering, athletes navigate an unmarked course using a map and compass, running rapidly on varied terrain. Elite orienteers demonstrate a high peak aerobic power,7 distinct abil­ity to run on steep inclines,8-9 and efficient running on difficult terrain.10-11 Accordingly, jump assessment in orienteering should show large correlations with the running performance of athletes, such as demonstrated in other sports involving running. However, to our knowledge, the current literature lacks such evidence for the sport of orienteering.

Since orienteering requires jumping over obstacles, running uphill and downhill, and responding to rapid changes in surfaces, the ability of the lower body to store and release elastic energy effectively—in combination with adequate levels of muscle strength, power, and endurance12—may also contribute to outstanding orienteering performance. In other sports, jumping and hopping

Hebert-Losier and Holmberg are with the Dept of Health Sciences, Mid Sweden University, Ostersund, Sweden. Jensen is with the Inst of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark. Address author correspondence to Kim Hebert-Losier at kim.hebert-losier@miun.se.

assessments can clearly differentiate between athletes with distinct abilities,2-3 for example, greater CMJ heights in sprinters than in endurance runners.3 Thus, jumping performances in elite orienteer­ing athletes could also differ from amateurs, for example, greater prestretch augmentation underlining a better functional use of the stretch-shortening cycle. However, these assumptions are yet to be verified.

Furthermore, the ranking of an orienteer during competition can be determined by a short, rapid sprint (eg, at the beginning of a mass start or during the final stretch toward the finish). Thus, short-distance sprints with rapid accelerations are highly pertinent in competitive orienteering. Currently, studies in this area typically involve 1.5- to 10-km distances,10-11 which might explain the lack of studies examining correlations between jumping and sprinting in orienteering, although such correlations have been reported in several other sports.4-6-13 Such information in orienteering might highlight desirable characteristics for athletes and assist in indi­vidualizing training programs.

With these considerations, the aims of the current investiga­tion were twofold. The first was to compare jumping and hopping performances between elite and amateur orienteer athletes, and the second was to investigate pairwise correlations between jumping and hopping, and sprinting and running performance. On the basis of previous findings from other sport disciplines, we hypothesized that the jump performance of elite orienteer athletes would differ from that of amateurs, with noticeable differences in vertical- and horizontal-jump heights and distances, peak forces, and stretch­shortening-cycle utilization. We anticipated large correlations between jumping and hopping, and sprinting and running, especially between peak countermovement forces and sprinting velocities, as well as between vertical stiffness and RE.

993

994 Hebert-Losier, Jensen, and Holmberg

Methods

SubjectsEight elite (mean±SDage 27.1 ±5.4 y,height 183.1 ±6.3 cm, mass 71.9 ± 6.0 kg) and 8 amateur (31.1 ± 8.9 y, 183.0 ± 4.1 cm, 73.8 ±8 .6 kg) male orienteer athletes provided their written informed consent before participating in this study. The elites ran -10.5 h/ wk (40% road, 35% path, 25% forest) and were all contenders for the Swedish National Orienteering Team. The amateurs ran -3.5 h/wk (25% road, 45% path, 30% forest) and were all members of a local recreational orienteering club.

The RE and peak aerobic power of subjects had recently (<1 mo) been tested while they ran on a treadmill according to standard incremental protocols.11 Briefly, the RE test involved series (3-6) of submaximal 4-minute runs with 1-minute rest periods using a 0% treadmill incline and increase in velocity of 1 km/h with each step. The attainment of a blood lactate concentration of at least 4 mmol/L at the end of a step was used to define the running veloc­ity at anaerobic threshold (vAt)- To assess peak aerobic power, an incremental treadmill-incline protocol was used starting with a 0% incline. After 2 minutes, this incline was increased by 2% and then by a further 2% every 90 seconds until exhaustion. Based on the RE test, the starting velocity was set so that each individual should be exhausted after 4 to 6 minutes.11 For the elites and amateurs, these velocities were 19.4 ± 0.5 km/h and 15.4 ± 0.7 km/h, and the actual times to exhaustion were 5 minutes 50 seconds ± 58 seconds and 5 minutes 24 seconds ±72 seconds, respectively.

For the respiratory measurements, a Douglas-bag system was used to collect expiratory gas continuously during the last minute of each step of the RE test and the last 2 to 3 minutes of the maxi­mal test using sampling times from 30 to 45 seconds. Heart rates were recorded continuously using a FS1-model heart-rate monitor from Polar Electro Oy (Kempele, Finland), and blood lactate con­centrations were measured within 60 seconds of each step of the RE test using a Biosen Sport C-Line blood-lactate analyzer (EKF- Diagnostic GmbH, Magdeburg, Germany) via 25-|±L samples taken from a fingertip. The RE at 15 km/h (RE|5km/h), vAt, and peak oxygen uptake ( V 0 2peak) of elites were 185.1 ± 8.7 mL • kg-1 • km-1, 18.6 ± 0.5 km/h, and 69.1 ± 2.6 mL • kg-1 • min-1, respectively. The cor­responding values in amateurs were 201.4 ± 5.5 mL ■ kg-1 • km-1, 15.0 ± 0.8 km/h, and 55.4 ± 3.1 mL • kg-1 ■ min-1. In both groups, the peak heart rate was 188 ± 6 beats/min.

DesignA repeated-measures design was employed that required subjects to attend 3 experimental sessions, 2 to 3 weeks apart, with the first 2 in the field and the third in a laboratory. All sessions were completed after the competitive orienteering season, with preapproval from the regional ethical review board (Umea, Sweden) and adherence to the latest amendments of the Declaration of Helsinki.

The 2-km RunsAfter a warm-up including 20 minutes of light running, short sprints, brief accelerations, and self-selected dynamic stretches, each subject ran one 2-km course each on a road, on a path, and in a forest as fast as possible. Each 2-km course was relatively flat (total climb -10 m), considered “easy” in terms of orienteering, delimited by brightly colored tape, randomized, and separated by 10-minute light­running recovery. To improve reproducibility of measures,14 subjects performed a familiarization run on these 2-km courses in training

the week before data collection. Acceptable reproducibility of time trials run off-road 7 days apart (ie, CV 2.3%) has been reported previously after initial familiarization with such time trials.14

Data-collection sessions were completed at 6 PM on a weekday with temperatures from 10°C to 12°C, overcast skies, and light precipitation. Each subject wore a global positioning system with a heart-rate monitor (Garmin Forerunner 305, Garmin International Inc, Olathe, KS, USA) sampling at 1 Hz. These data were extracted using QuickRoute Software version 2.3 (freely available for down­load at http://www.matstroeng.se/quickroute/en/index.php) and used to determine the mean velocity (total distance divided by time, in m/s) and heart rate (normalized to peak heart rate, in %) for each 2-km course. Respiratory measurements were not collected during the field test because of lack of access to a portable gas-exchange analyzer.

The 20-m SprintsAfter a 10-minute warm-up similar to the 20-minute one described for the 2-km runs, each subject sprinted 3 X 20 m as fast as possible, once on a road, once on a path, and once in a forest, to assess the running velocity during the acceleration phase of sprint running. Each sprint was on a level surface and followed by 2-minute walk­ing recovery. Each set of 3 x 20-m sprints was randomized, with 5 m to minor the effect of the initial steps toward sprint acceleration and over 10 m for deceleration. High levels of reproducibility of 20-m-sprint performance (ie, CV 1.9% across 5 sessions) have been reported, without need for familiarization.15

Sprints were completed during 1 weekend with temperatures from 7°C to 11°C, clear skies, and no precipitation. An equal number of elites and amateurs were tested in the morning and afternoon. Sprint times were recorded using a timing-gate system (MuscleLab version 8, Ergotest Innovation AS, Porsgrunn, Norway) with paired photoelectric sensors (model WL170-N132, SICK AG, Waldkirch, Germany) placed on 1-m-high tripods at the start and end of each sprint. Sprint times were converted to velocities (m/s), with the quickest sprint on each surface subsequently analyzed. Subjects were asked to wear their usual running shoes during all running trials, using the same footwear in the 20-m sprints, 2-km runs, and treadmill testing procedures.

The Jumping and Hopping TestsStandard familiarization and testing methods were employed to assess jumping16 and hopping,17 which have been described in detail previously16-17 and therefore only summarized here. At the laboratory, each subject watched a video that visually demonstrated and verbally described the proper performance of the jumping and hopping tests. Subjects then performed a light-intensity 5-minute warm-up running on a treadmill (model RL 2500E, Rodby Innova­tion AB, Vange, Sweden), practiced the jumping and hopping tests under the supervision and guidance of the principle investigator, and took a 2-minute rest before testing.

A calibrated force plate (Kistler, Winterthur, Switzerland) sampled ground-reaction forces at 1000 Hz during jumps and hops using MARS version 1.0.3 (S2P Ltd., Ljubljana, Slovenia) and built- in modules for squat jump (SJ), CMJ, standing long jump (SLJ), and repetitive hopping (HOP). Subjects completed 3 trials of each task interspersed by 2 minutes of rest, zeroing the force plate before each trial. Since footwear can influence the human-ground inter­actions during ground contact18 and jump performance,19 subjects were barefoot with hands on hips, feet shoulder width apart, and

Jumping and Running in Orienteering 995

eyes directed forward in all jumping and hopping trials. If subjects failed to perform a trial adequately (eg, hands were not maintained on hips), it was replaced with another trial after a 2-minute rest.

For SJs, subjects jumped (vertically) as high as possible from a static squat position with the hips and knees flexed to -90° (ie, 180° being upright stance with the trunk, femur, and tibia aligned). For CMJs, subjects jumped (vertically) as high as possible from erect standing using a prior downward countermovement motion. In both cases, subjects were told to land in a position similar to takeoff (ie, with the knees straight and the ankles plantar flexed). For SLJs, subjects jumped (horizontally) forward as far as possible from an erect standing position, using a prior countermovement and without falling backward on landing. No particular specifications were provided regarding the depth or velocity of all countermove­ment motions.

The single jumps with the greatest vertical SJ height (ASJ, in cm), vertical CMJ height (hCm »in cm), and horizontal displacement of the center of gravity during SLJ (dSu, in cm) were identified using MARS based on the takeoff velocities. The peak force relative to body weight (/peak> in % BW), peak power relative to body weight (Ppeak, in W/kg), and time to peak force (rpeak, in s) associated with these jumps were extracted. The prestretch augmentation (PSA, in %) was computed according to Walshe et al2() using the equation ( ^ c m j - hsj)/hsj-

For HOPs, subjects hopped (vertically) first on both legs, then once on the right and once on the left in randomized right-to-left order. They were instructed to act as springs during hopping, keep their knees straight, land in a position similar to takeoff (ie, with the ankles plantar flexed), keep in pace with a metronome, and minimize ground contact during hops to limit secondary move­ments in other joints. Each trial consisted of 33 successive hops performed at 2.2 Hz indicated audibly by the TempoPerfect© v. 2.02 computerized metronome (NCH Software, Canberra, Australia). The ground-reaction-force data extracted by MARS were treated in MATLAB (The MatWorks, Inc, Natick, MA, USA), converting the force curves to vertical accelerations using the subjects’ mass and gravitational acceleration (g = 9.82 m/s2).17 Acceleration curves were then integrated twice to yield velocities and positions using central difference expressions, evaluating velocities (v) halfway between accelerations (a) and positions (p) with a time step of At = 0.001 second. The initial position and velocity integration constants were defined stating a zero vertical position of the center of mass at initial ground contact and takeoff, respectively.

Leg stiffness (k) was computed as the ratio between the maximal vertical upward ground-reaction force (fmax) and maximal vertical downward displacement of the center of mass (pmax) during ground contact as k = /max/pmax. Stiffness was calculated from each of the 33 hops, sorted in an ascending order, and the mean of the medial 22 of the 33 values extracted to provide a unique k value from the 2-leg (&both), right-leg (£right), and left-leg (fcleft) trials.17 All jump and hop variables derived here have demonstrated generally acceptable between-days reproducibility,16 with an average CV of 8.5% (range 3.3-19.1%), with rpeak showing the highest CV.

Data AnalysisMean ± SD were computed for all variables to describe the data. To limit bias arising from nonuniformity of error,21 log-transformed values (except for the PSA, which contained negative numbers and could not be log-transformed) were used during analysis. No P-value statistics were calculated considering the inherent limitations linked to significance testing and their dependencies on sample size.22

Instead, between-groups comparisons of means were performed using a modified statistical spreadsheet and inferential statistics that emphasize precision of estimation rather than null-hypothesis testing.23

Magnitude-based inferential statistics were calculated using appropriate between-subjects SD values, with 0.20 of these standard deviations indicating the smallest worthwhile difference in means.24 Magnitudes of the standardized effects (ES) were interpreted using thresholds of 0.2, 0.6, 1.2, and 2.0 for small, moderate, large, and very large differences, respectively.21 ESs between -0.19 and 0.19 were considered trivial. The chance that the true value of the ES was practically meaningful was evaluated qualitatively as follows: <1%, almost certainly not; 1% to 5%, very unlikely; >5% to 25%, unlikely; >25% to 75%, possible; >75% to 95%, likely; >95% to 99%, very likely; >99%, almost certain.23 An effect was deemed clear if its confidence interval did not overlap the thresholds for small positive and small negative effects (ie, 5%).

Finally, pairwise correlations between jumping and hopping variables and those from the 20-m sprints, 2-km runs, and baseline values for REi5km/h, v At, and V 0 2pCak were examined using Pearson product-moment correlation coefficients (r). Magnitudes of r were interpreted using thresholds of .1, .3, .5, and .7 for small, moderate, large, and very large correlations, respectively.21 All data processing and analyses were performed using Microsoft Excel 2010 (Microsoft Corp, Redmond, WA, USA).

ResultsTable 1 summarizes jumping and hopping variables and results from the between-groups comparison of means. Overall, moderate and clear between-groups differences were observed in SJ and CMJ performances. Despite moderately lower hS], possibly smaller /rCMJ, and possibly to likely lower />peak, the elites exhibited greater PSA, higher / peak, and shorter fpeak in these 2 vertical-jump tests. With the exception of a moderately shorter tpeak in elites during SLJs, no clear between-groups differences were discerned in SLJ and HOP performance.

Descriptive summaries of sprinting and running performance are provided in Table 2, and their correlations with jumping and hopping variables in Table 3. On the 2-km time trials, the mean heart-rate values recorded were 94% ± 3% of peak heart rate, with no clear differences between elites and amateurs.

For the most part, the/peak and associated with the 3 jumpingtasks exhibited moderate to large correlations with the 20-m-sprint velocities of subjects, with greater/peak and shorter rpeak observed in faster sprinters. The SJ parameters were more closely related to the forest sprints, while those from the CMJ and SLJ to the road or path sprints.

Correlations between jumping tests and 2-km-running veloci­ties were generally weaker, being the largest between the running velocities and the hsj, tpeak of the SJ, ?peak of the CMJ, and PSA. The p peak parameter showed moderate correlations at best, with strongest correlations between the 2 vertical p peak values and the 2-km-running velocities on the path and between the horizontal p peak and the 20-m-sprint velocities on the road and on the path. Higher vertical /7peak was associated with slower 2-km running velocities, but higher horizontal p pcak with faster 20-m sprints.

With regard to the baseline values acquired on a treadmill, triv­ial or small correlations were observed between all jump measures and subjects’ RE |5/km. T h e /peak and rpeak during the CMJ exhibited the largest correlations with the vAT, with h igher/peak and shorter tpeak observed with faster vAT. The rpeak of the SJ, rpeak of the CMJ,

996 Hebert-Losier, Jensen, and Holmberg

Table 1 Performance of Squat Jump, Countermovement Jump, Standing Long Jump, and Repetitive Hopping by Elite and Amateur Orienteer Subjects, Mean ± SD

Test Parameter Elite (n = 8) Amateur (n = 8) ES (magnitude) Chance of meaningful difference

Squat jump hss (cm) 29.0 ±5 .1 32.5 ± 4 .2 0.75 (moderate) 87% (likely, clear)

/peak (% body weight) 258.1 ±31.9 232.4 ± 20.5 -0 .89 (moderate) 91% (likely, clear)

Ppeak (W/kg) 48.6 ± 5 .7 51.0 ±4.3 0.47 (small) 71% (possible, clear)

p̂eak (ms) 193 ± 63 243 ± 59 0.80 (moderate) 89% (likely, clear)

Countermovement jump hCMs (cm) 31.2 ±3.5 32.4 ± 4.4 0.27 (small) 55% (possible, unclear)

/peak (% body weight) 241.7 ±27.0 224.7 ± 14.0 -0 .72 (moderate) 86% (likely, clear)

Ppeak (W/kg) 44.8 ±4.9 47.3 ± 3.9 0.53 (small) 75% (likely, unclear)

tpeak (HIS) 577 ± 102 662 ± 90 0.87 (moderate) 91% (likely, clear)

(% ) 9.2 ± 13.3 -0.3 ± 9.0 -0.78 (moderate) 88% (likely, clear)

Standing long jump dcoc (cm) 81.1 ± 10.0 82.6 ± 10 0.14 (trivial) 45% (possible, unclear)

/peak (% body weight) 67.7 ± 6.8 68.7 ±8 .7 0.10 (trivial) 41% (possible, unclear)

Ppeak (W/kg) 13.4 ± 2 .0 13.6 ±3.1 0.01 (trivial) 34% (possible, unclear)

p̂eak (ms) 7 3 8 ± 151 906 ± 240 0.67 (moderate) 83% (likely, clear)

Repetitive hopping kboth (kN/m) 30.5 ± 6 .8 30.6 ± 10.1 -0 .09 (trivial) 41% (possible, unclear)

bright (kN/m) 18.5 ± 3 .0 19.4 ± 4 .4 0.15 (trivial) 46% (possible, unclear)

fcieft (kN/m) 18.6 ± 2 .4 19.5 ± 4 .6 0.14 (trivial) 45% (possible, unclear)

Abbreviations: ES, standardized effect; hSi, vertical-squat-jump height;/p^, peak force relative to body weight; p ^ , peak power relative to body weight; t ^ , time to peak force; hCUh vertical-countermovement-jump height; PSA, prestretch augmentation; 4cog> horizontal-standing-long-jump displacement of the center of gravity; kb0fll, stiffness during hopping on both legs; krigh„ stiffness during hopping on the right leg; kieft, stiffness during hopping on the left leg.

Note: The magnitudes of the ES and chances of practically meaningful differences for the between-groups comparison of means are provided. Between-groups comparisons were performed on the log-transformed values (except for PSA where the raw data contained negative values). Magnitudes of the ES were interpreted using thresholds of < 0.2, 0.2, 0.6, 1.2, and 2.0 for trivial, small, moderate, large, and very large, respectively.21 The effect was clear when its 95% confidence interval did not overlap the thresholds for small positive and small negative effects. Quantitative chances of a practically meaningful ES were evaluated as <1%, almost certainly not; 1-5%, very unlikely; >5-25%, unlikely; >25-75%, possible; >75-95%, likely; >95-99%, very likely; >99%, almost certain.23

Table 2 Velocity (m/s) in the 20-m Sprints and 2-km Runs by Elite and Amateur Subjects, Mean ± SD

Test Condition Elite (n = 8) Amateur (n = 8) ES (magnitude) Chance of meaningful difference

20-m sprint Road 7.6 ± 0 .2 7.0 ± 0 .4 -1 .59 (large) >99% (almost certain, clear)

Path 7.3 ± 0 .2 6.8 ±0 .3 -2 .06 (very large) >99% (almost certain, clear)

Forest 7.0 ± 0 .4 6.3 ±0 .3 -1.96 (large) >99% (almost certain, clear)

2-km run Road 5.6 ± 0 .2 4.5 ± 0.2 -4.21 (very large) >99% (almost certain, clear)

Path 4.6 ± 0 .2 3.7 ± 0.2 -4 .06 (very large) >99% (almost certain, clear)

Forest 3.7 ± 0 .2 2.9 ± 0 .2 -4 .64 (very large) >99% (almost certain, clear)

Abbreviation: ES, standardized effect.

Note: Between-groups comparisons were performed on the log-transformed values. Magnitudes of the ES were interpreted using thresholds of <0.2, 0.2, 0.6, 1.2, and 2.0 for trivial, small, moderate, large, and very large, respectively.21 The effect was clear when its 95% confidence interval did not overlap the thresholds for small positive and small negative effects. Quantitative chances of a practically meaningful ES were evaluated as <1%, almost certainly not; 1-5%, very unlikely; >5-25%, unlikely; >25-75%, possible; >75-95%, likely; >95-99%, very likely; >99%, almost certain.23

PSA, and h Si were the most strongly correlated to V 02peak, showing moderate correlations. Similar to results from the field tests, the of jumps showed moderate correlations at best with the laboratory measures, with more powerful subjects exhibiting lower V02peak- All HOP variables exhibited small to trivial correlations with the 20-m sprints, 2-km runs, and treadmill-test variables, except for the / right of athletes demonstrating moderate correlations with the V 02peak.

Discussion

Our primary aim was to compare the jumping and hopping perfor­mance of elite and amateur orienteer athletes. As could be antici­pated, the relative peak vertical forces, PSA (indicator of stretch- shortening-cycle functional utilization), and times to peak vertical and horizontal forces were all clearly superior in elites. In contrast,

Ta

ble

3

Inte

rco

rre

lati

on

Ma

trix

Be

twe

en

th

e P

erf

orm

an

ce

Du

rin

g J

um

pin

g a

nd

Ho

pp

ing

an

d t

he

20

-m S

pri

nts

, 2

-km

Ru

ns

, a

nd

Ba

se

lin

e R

un

nin

g

Ec

on

om

y a

nd

Pe

ak

Ox

yg

en

-Up

tak

e V

alu

es

of

the

Ori

en

tee

r S

ub

jec

ts (

N =

16)

, r

(ma

gn

itu

de

)

1—

* ECO T3O Q 73O 73O 13 1373O 73O® • 0.1- g g E E £

(A

OO

E E §CV 1o D) O CN 'w/ CA ^^

7}- »/7> oc

rcnr r CN cnr

7t1*

E€ ■ *E •2* T-in i

LLI vcc .

c/>1

ic/>

Q.</)

73O£

03E E

00 CN (N

—̂'13a

73OChCA £'w'

oCN rn

13*>f i1/7O

r

CNCn

T 3 13 13 13 -oCi 13

EO

gEC/3 ECA ECA

og

Ec/j g

VO 7f VO \ > i/7 ON CN ^mCNcn CN

f rCN

rTt CN

\ f

.2’>fi

.2*cVOo

2'SOn U7o —:

d ■ —' C3 13E - r E E

_d

'S

73OS,CN7f

00CN

73O£

CNIT)f

73O

g

ONPf

_2

’ >■oo

313E(A

73Og

0)S2

"£>

f i

[d’ >

g

13

g

73OE. ‘C

2’>g

ooo

oop

00CNr

OnT t

rop o

oTj-o

ooo

7j-r

ooo

7 fo

73§

73O£

73o

ON7fI I

d£C/3

n— ✓

CNf

3’>'SCN O O CN

OJOJD 13 13 13

T3CO_o E,o

g J . EC/3 ECAo£^

E’■A

S-J j

og

EC/2>

'S>

;s 1 . ficnf

cnr

cn r - cn VO CN 1/7 cn l/7 w 'p CN

1 17 t CN

1m

Icn

1o

io1 f p

I I

r

s3t"irj

>f iONof

73o

cnCN r-ITi

r

73 13 3q 13 13 o 13E,

1•g £C/D £CA E, £00

’ >f i

cn1-4-^ ^ —̂' o V '

ON 71; 00 7 f CN 7t*xT o p p r p o

'oTDID 3 o 3 0)

OJD3 DID 13•-

.2IT)

*>'S

CN

§

cncn

’>TJ

VO

fasVO

'S _d

cnvq

EOO

Tfp O f O vq o p

73o

73o

OJDfa_2cnIT)

CO

£%a>

*d (HcuOJD "2

VOJDfa T5

Eoo£C/5 E fa

J2 £on -2 EC/5

a

73O

73O

O1/7

£ £

VOCNf

t"voCNVO 7j-CN

oo

73O

5

d

fioo >n o o

(cm

) CQ

--s00

BO

m'bJD ? E

|onE, £

onE, £ £ £

CAB

Zg , § ,

c3a

^4 1su ■a

4Sa. 1^o.

<Oh "̂ 3

1• 4

1o.o .

1Q.o £

sU cn

cuOSC

O NCN

O■st 833 00m ooin

*d "2 2C7 2 .2 P ’> ■> ’>E ’> •r-<

oc g 'fi f icn *S f i , fa'—' 7t in 7fr- vo VO 17

p o O Op O o r r 1*

d’>'3,r-o

>•c

o

CN 1 1— 1

2’>3cno

.a <jO OO £ ^ a +-« JZ qj b£)■5 ’SH ,•C S

7 3 03 CD CD

1 *O <Do ><d•— A<D 2j2 p2 MQ,3C

a

8a -2.S '§o g<D > o

CD-Cbo- CD

I O o 8 > i-r2 ^o U

P 8.

I !>> „

IoO13 is> JC A bO

£ 1 C 73

£> •n o

03 <0>>’C £ -2 o p

<D >g? a 1 - a§ a c =*■

I 13 a.W ~04 fois § e 1 fi-S 103 O C ^— o

. d <D CD >

> £2> 8

• f i5 <u

8 M 13 «■5 002?" 13.. o T3 ■■p 03 w

o3

8*1 i£ •5 |<D duI : -

C iT O w

997

pres

tretc

h au

gmen

tatio

n; S

LJ, s

tand

ing

long

jum

p; cf

coG,

hor

izon

tal S

LJ d

ispl

acem

ent o

f the

cen

ter o

f gra

vity

; £bo

ih, s

tiffn

ess d

urin

g 2-

leg

hopp

ing;

Arig

ht, s

tiffn

ess d

urin

g rig

ht-le

g ho

ppin

g; /c

iefl,

stiff

ness

dur

ing

left-

leg

hopp

ing.

Not

e: M

agni

tude

s of

Pea

rson

pro

duct

-mom

ent c

orre

latio

n co

effic

ient

s (r

) w

ere

inte

rpre

ted

usin

g th

resh

olds

of 0

.1,0

.3, 0

.5, a

nd 0

.7 f

or s

mal

l, m

oder

ate,

larg

e, a

nd v

ery

larg

e co

rrel

atio

ns, r

espe

ctiv

ely.

21 Th

e R

Ei5k

m/h

data

an

alys

es a

re o

n 7

amat

eurs

bec

ause

1 am

ateu

r did

not

reac

h th

e 15

-km

/h th

resh

old.

Lar

ge c

orre

latio

ns a

re in

bol

d.

a Mea

sure

s ob

tain

ed fr

om tr

eadm

ill ru

nnin

g te

sts f

ollo

win

g st

anda

rdiz

ed in

crem

enta

l pro

toco

ls.11

998 Hebert-Losier, Jensen, and Holmberg

in the purely concentric lower-body SJ test, the elites jumped lower than amateurs and developed slightly less peak power relative to body weight. These latter findings most likely reflect muscle adapta­tions resulting from the more extensive endurance training of our elites; for example, higher endurance is associated with a larger proportion of slow-twitch lower-body muscle fibers.12,25 However, such adaptations did not hinder the ability of our elite subjects to develop high relative peak forces rapidly during both the squat and the CMJs, consistent with previous studies involving elite athletes where increases in strength did not necessarily translate into greater power.26 The peak force of our elites during jumping was probably reached at a moment of lower velocity and, in combination with shorter push-off times, explains why their tpeak was shorter and/peak higher, without a more pronounced p peak.

Unexpectedly, the between-groups differences with respect to SLJ distance,/peak, and p peak, as well as hopping stiffness, were trivial and unclear. The lack of difference in the SLJ may be linked to its complexity, with the total horizontal distance largely influ­enced by the takeoff angle and jump technique.27 Furthermore, although parameters derived from ground-reaction forces during jumps are used as the “gold standard” reference for quantify­ing performance,28 the between-sessions reproducibility of such parameters derived from horizontal jumps is generally lower than that of vertical jumps.16 Therefore, identifying and interpreting differences in force-derived parameters might be more challenging for the horizontal SLJ.

Nonetheless, the fact that the relative peak vertical, but not horizontal, jump force was greater in our elites than amateurs may simply reflect the importance of vertical lower-body strength in orienteering. Indeed, these findings are consistent with the reported pronounced ability of high-performing orienteering athletes to run uphill.8,9 Earlier research involving members of the Swiss National Orienteering Team revealed that those who ran more rapidly uphill tended to place better during world championships.8 More recent investigations indicate that the correlations between the V02peak and maximal running velocities of national-level orienteering ath­letes are larger when tested at an extreme 22% treadmill incline (r = .845, P < .01) than on a flat treadmill (r = .46, P > ,32).9 Since running uphill augments ground-reaction forces and activation of leg-extensor muscles,29 it appears reasonable that our elites showed superior/peak during the vertical jumps, a characteristic that could assist uphill running.

The lack of differences in hopping stiffness may be due to several factors. For one, running was the primary mode of exercise for all our orienteer athletes.2 Moreover, the use of a simple spring- mass model to characterize human motion has inherent limitations17; for example, the model does not consider the neural mechanisms regulating stiffness. At a more defined level, differences between groups might have been discerned, for example, by ultrasound30 or free oscillation1,20 procedures.

That being said, enhanced stiffness generally exerts a negative impact on PSA and functional use of the stretch-shortening cycle. The latter trait may be more beneficial than increased vertical stiffness for orienteering athletes, who must respond rapidly to alterations in running terrain and obstacles. Ultrasound-imaging evidence suggests that intricate muscle-tendon interactions con­tribute to the effective use of the stretch-shortening cycle in the lower body, with lower tendon stiffness actually characterizing competitive long-distance runners.30 Indeed, Kubo et al30 suggest that more compliant lower-limb tendons may prevent fatigue, since the tendinous structures absorb impact shocks, and allow lower shortening velocities of muscle fibers.

Our second aim was to investigate correlations between jump­ing and hopping and between sprinting and running performance in orienteering athletes. Similar to observations by Markstrom and Olsson,6 the countermovement/peak and 20-m-sprint velocities of our athletes exhibited strong positive correlations. However, leg stiffness in our study exhibited no large correlations with any of the sprinting or running variables, contrasting with previous findings that hopping stiffness correlates closely with RE5 and maximal 40-m-sprint velocities13 and predicts performance during the latter stages of a 100-m sprint,13 but agreeing with indications that stiffness does not influence performance during 5-m and 10-m accelerations and sprints.31 In combination with the limitations of the spring-mass model discussed herein, the specific sprinting and hopping variables, different computational methods, and types of subjects involved might explain the discrepancies in study findings.

At the same time, large pairwise correlations were observed here between the relative peak SJ and CMJ forces and 20-m-sprint velocities; between the fpeak during the SJs, CMJs, and SLJs and the 20-m-sprint and 2-km-running velocities; and between the PSA and the 2-km-running velocity in the forest. Although correlations between jumping and hopping performance and treadmill-based RE, vAt, and V02peak were weaker—in support of previous state­ments that laboratory measures are not always valid indicators of orienteer performance12—moderate correlations still suggest that V 02peak and vAT were higher in orienteers exhibiting greater PSA, shorter fpeak, and superior/peak during SJs, despite lowerppeak. Thus, the orienteering athletes who exhibited a better functional utiliza­tion of their stretch-shortening cycle and greater ability to generate high relative peak forces in a shorter time were also most often the ones with better sprinting, running, and aerobic capacities, indicat­ing the value of testing and training lower-body muscles in such athletes. Accordingly, the incorporation of lower-body plyometric exercises, which require use of the stretch-shortening cycle, quick movements, and rapid generation of high forces,32 into orienteering training might be beneficial for performance.

Considering both the magnitudes of the standardized effects and correlation coefficients, it could be speculated that short tpeak is the most important for running in orienteering, more than/peak,ppeak, and jump height or distance. On the other hand, the jump-related between-groups differences detected were much smaller than those relating to the 20-m sprints and 2-km runs and obviously those at baseline for REi5km/h, vAt, and V 02peak. Indeed, separately analyzing these variables reveals effect sizes that are very large (2.1 to 4.5) and almost certainly meaningful. Consequently, although lower-body strength, power, and endurance are factors that may contribute to orienteering performance, high maximal aerobic capacity7 and efficient running10,11 are physical attributes essential for successful orienteering. Finally, we also acknowledge that the low number of subjects limits our ability to generalize results and make unequivo­cal conclusions concerning differences in jumping and hopping abilities of elite and amateur orienteer athletes. Nonetheless, our results provide a basis that future research work may extend on, assist in guiding coaches and training requirements in orienteering, and contribute to the identification of factors that promote high performance in this sport.

Practical Applications and ConclusionsJump tests are used in several sports to assess lower-body power, vertical stiffness, and stretch-shortening-cycle utilization, with many studies reporting substantial correlations between jumping and sprinting or running performance. Here, we found that differ-

Jumping and Running in Orienteering 999

ences between elite and amateur orienteer athletes were greater in connection with squat and CMJs than with standing horizontal long jumps and repetitive hopping. Despite lower SJ and CMJ heights and relative peak powers, our elites demonstrated superior relative peak forces, shorter times to peak force, and better PSA, and these measures were correlated with sprinting, running, and aerobic per­formance, indicating a benefit of lower-body testing and training in orienteering. Accordingly, incorporating plyometric exercises, especially involving vertical motions, might benefit orienteering performance since plyometrics rely on stretch-shortening-cycle utilization and the rapid development of high forces.

Acknowledgments

The authors acknowledge the support of Peter Oberg and Ola Jodal during the field-testing procedures. The authors thank Fredrik Edin and Kurt Jensen for providing the baseline values from laboratory testing of run­ning economy and peak oxygen uptake. We also thank Professor Claes Annerstedt for allowing us to use the laboratory testing facility at the University of Gothenburg.

References1. Dumke CL, Pfaffenroth CM, McBride JM, McCauley GO. Rela­

tionship between muscle strength, power and stiffness and running economy in trained male runners. Int J Sports Physiol Perform. 2010;5(2):249—261. PubMed

2. Hobara H, Kimura K, Omuro K, et al. Determinants of difference in leg stiffness between endurance- and power-trained athletes. J Biomech. 2008;41 (3):506—514. doi:10.1016/j.jbiomech.2007.10.014

3. Harrison AJ, Keane SP, Coglan J. Force-velocity relationship and stretch-shortening cycle function in sprint and endurance athletes. J Strength Cond Res. 2004; 18(3):473-479. PubMed

4. Maulder P, Cronin J. Horizontal and vertical jump assessment: reli­ability, symmetry, discriminative and predictive ability. Phys Ther Sport. 2005;6(2):74-82. doi: 10.1016/j.ptsp.2005.01.001

5. Dalleau G, Belli A, Bourdin M, Lacour JR. The spring-mass model and the energy cost of treadmill running. Eur J Appl Physiol Occup Physiol. 1998;77(3):257—263. PubMed doi:10.1007/s004210050330

6. Markstrom JL, Olsson C-J. Countermovement jump peak force rela­tive to body weight and jump height as predictors for sprint running performances: (in)homogeneity of track and field athletes? J Strength Cond Res. 2013 ;27(4):944-953. doi:10.1519/JSC.0b013e318260edad

7. Jensen K, Johansen L, Secher NH. Influence of body mass on maximal oxygen uptake: effect of sample size. Eur J Appl Physiol. 2001 ;84(3):201-205. doi:10.1007/s004210170005

8. Ziircher S, Clenin G, Marti B. Uphill running capacity in Swiss elite orienteers. Sci J Orienteer. 2005; 16( 1):4—11.

9. Lauenstein S, Wehrlin J, Marti B. Differences in horizontal versus uphill running performance in male and female Swiss world class orienteers. J Strength Cond Res. 2013;27(11):2952—2958. doi:10.1519/ JSC.0b013e31828bf2dc

10. Smekal G, Von Duvillard SP, Pokan R, et al. Respiratory gas exchange and lactate measures during competitive orienteering. Med Sci Sports Exerc. 2003;35(4):682—689. doi: 10.1249/01.mss.0000058358.14293.de

11. Jensen K, Johansen L, Karkkainen OP. Economy in track run­ners and orienteers during path and terrain running. J Sports Sci. 1999; 17( 12):945—950. doi:10.1080/026404199365335

12. Rolf C, Andersson G, Westblad P, Saltin B. Aerobic and anaero­bic work capacities and leg muscle characteristics in elite ori­enteers. Scand J Med Sci Sports. 1997;7( 1 ):20—24. PubMed doi: 10.1111/j. 1600-0838.1997.tb00112.x

13. Bret C, Rahmani A, Dufour AB, Messonnier L, Lacour JR. Leg strength and stiffness as ability factors in 100 m sprint running. J Sports Med Phys Fitness. 2002;42(3):274—281. PubMed

14. Easthope CS, Nosaka K, Caillaud C, Vercruyssen F, Louis J, Briss- walter J. Reproducibility of performance and fatigue in trail run­ning. J Sci Med Sport. 2014; 17(2):207-211. PubMed doi: 10.1016/j. jsams.2013.03.009

15. Moir G, Button C, Glaister M, Stone MH. Influence of familiarization on the reliability of vertical jump and acceleration sprinting perfor­mance in physically active men. ] Strength Cond Res. 2004; 18(2):276— 280. PubMed

16. Hebert-Losier K, Beaven CM. The MARS for squat, countermove­ment and standing long jump performance analyses: are measures reproducible? J Strength CondRes. 2014;28(7): 1849-1857. PubMed doi: 10.1519/JSC.0000000000000343

17. Hebert-Losier K, Eriksson A. Leg stiffness measures depend on com­putational method. J Biomech. 2014;47(1): 115—121. doi: 10.1016/j. jbiomech.2013.09.027

18. Bishop M, Fiolkowski P, Conrad B, Brunt D, Horodyski M. Ath­letic footwear, leg stiffness, and running kinematics. J Athl Train. 2006;41 (4):387—392. PubMed

19. LaPorta JW, Brown LE, Coburn JW, et al. Effects of different foot­wear on vertical jump and landing parameters. J Strength Cond Res. 2013;27(3):733—737. doi:10.1519/JSC.0b013e318280c9ce

20. Walshe AD, Wilson GJ, Murphy AJ. The validity and reliability of a test of lower body musculotendinous stiffness. Eur J Appl Physiol. 1996;73(3^1):332-339. doi:10.1007/bf02425495

21. Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41 (1):3-13. doi:10.1249/MSS.0b013e31818cb278

22. Levine TR, Hullett CR. Eta squared, partial eta squared, and misre- porting of effect size in communication research. Hum Commun Res. 2002;28(4):612-625. doi:10.1111/j.1468-2958.2002.tb00828.x

23. Hopkins WG. A spreadsheet for analysis of straightforward controlled trials. SportScience, 2003:7.

24. Cohen J. Statistical Power Analysis fo r the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum; 1988.

25. Abemethy PJ, Thayer R, Taylor AW. Acute and chronic responses of skeletal muscle to endurance and sprint exercise: a review. Sports Med. 1990;10(6):365-389. PubMed doi: 10.2165/00007256-199010060- 00004

26. Baker D. Comparison of upper-body strength and power between professional and college-aged rugby league players. J Strength Cond Res. 2001; 15(1): 30—35. PubMed

27. Wakai M, Linthorne NP. Optimum take-off angle in the stand­ing long jump. Hum Mov Sci. 2005;24(1):81—96. doi:10.1016/j. humov.2004.12.001

28. Reeve TC, Tyler CJ. The validity of the SmartJump contact mat. J Strength Cond Res. 2013;27(6): 1597-1601. doi:10.1519/ JSC.0b013e318269f7fl

29. Padulo J, Powell D, Milia R, Ardigo LP. A paradigm of uphill running. PLoS One. 2013;8(7):e69006. doi: 10.1371/journal.pone.0069006

30. Kubo K, Tabata T, Ikebukuro T, Igarashi K, Yata H, Tsunoda N. Effects of mechanical properties of muscle and tendon on performance in long distance runners. Eur J Appl Physiol. 2010;110(3):507-514. doi: 10.1007/s00421-010-1528-1

31. Lockie R, Murphy A, Knight T, Janse de Jonge X. Factors that dif­ferentiate acceleration ability in field sport athletes. J Strength Cond Res. 2011 ;25(10):2704-2714. doi:10.1519/JSC.0b013e31820d9fl7

32. Markovic G, Mikulic P. Neuro-musculoskeletal and performance adaptations to lower-extremity plyometric training. Sports Med. 2010;40(10):859—895. doi: 10.2165/11318370-000000000-00000

Copyright of International Journal of Sports Physiology & Performance is the property ofHuman Kinetics Publishers, Inc. and its content may not be copied or emailed to multiplesites or posted to a listserv without the copyright holder's express written permission.However, users may print, download, or email articles for individual use.